Scientometrics Workshop
at the Extended Semantic Web Conference (ESWC) 2017
May 28th, 2017
Abstract
Scientometrics is a field of research that analyses and measures science and technology research and innovation. When it comes to scientometrics the Semantic Web community has both much to offer and much to gain. On the one hand, we are very well positioned to integrate and analyse the complex data that is needed in order to push the field forward. On the other, we need to demonstrate the impact we as researchers and we the Semantic Web community have one academia, business and society. With this workshop we have identified a critical mass of people that are interested in scientometrics and aim to build a community, whose function is to identify research challenges and opportunities, align our research efforts and encourage the broader Semantic Web community to apply their existing tools and technologies to the field of scientometrics.
Motivation and Objectives
The Semantic Web has been an area of intense research for many years. Over the years there has been a number of papers that provide insight into research topics and trends within the Semantic Web community (Berners-Lee et al., 20011 , Feigenbaum et al., 20092 , Bernstein et al., 20163 ). At the same time there have been several initiatives that aim to make research data more accessible (Semantic Web Dog Food, Microsoft Academic Search, DBLP, Scholarly Data, Linked Research) and a number of tools have emerged that allow us to gain insights into the topics, people and organisations that define our community (Rexplore, Saffron, SWJPortal).
In order to analyse the characteristics of scientific research and the mechanisms by which scientific results are disseminated to academia, business and society, analysis of complex data is required. Besides citation networks, scientific communities are interconnected by co-working relations, co-organisation of events, participation in projects and excellence networks. The entities involved are manyfold (scientists, organisations of different types -academia, research institutes, industry, publishers-, events and venues, publications, locations, projects, funding agencies, etc.) and consequently the research topics that are themselves highly interconnected span these complex networks. The tools required for modelling, storing and reasoning on top of such complex and interconnected data have been long researched in the Semantic Web community. Consequently, our community is ideally positioned to integrate and analyse the complex data that is needed in order to push the scientometrics field forward.
Furthermore, much more could be done in terms of: automatically analysing the impact we as a community have on science and engineering; tracking the diffusion of topics between different research communities and into industry; and using alternative means to measure researcher impact beyond traditional measures such as paper output and impact in terms of citations. The first step is to make more data on community activities available (e.g. editorship, organising committee, program committee, academic lineage, industry white papers, participation in dataset/ontology/tool development, etc…) and the second is to better understand what we as a community can offer in terms of scientometrics.
As such, the goals of the workshop are threefold:
(i) to consolidate existing research efforts that focus on research data publishing and topic, trend and community analysis;
(ii) to identify existing tools and techniques that can be used to identify trends, to examine the diffusion of topics between academia to industry, and to measure the impact that our research has on society and business; and
(iii) to demonstrate what our community can contribute to scientometrics on a much broader scale, beyond the Semantic Web Community.